{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "# using python 3.6"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Word2Vec"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "https://www.tensorflow.org/tutorials/word2vec"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 41,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "\"\"\"Importing the required packages\"\"\"\n",
    "import random\n",
    "import collections\n",
    "import math\n",
    "import os\n",
    "import zipfile\n",
    "import time\n",
    "import re \n",
    "\n",
    "import numpy as np\n",
    "import tensorflow as tf\n",
    "\n",
    "from matplotlib import pylab\n",
    "%matplotlib inline\n",
    "\n",
    "from six.moves import range\n",
    "from six.moves.urllib.request import urlretrieve\n",
    "\n",
    "from tensorflow.contrib.tensorboard.plugins import projector\n",
    "%config InlineBackend.figure_format = 'retina'\n",
    "\n",
    "import matplotlib.pyplot as plt\n",
    "from sklearn.manifold import TSNE"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "\"\"\"Make sure the dataset link is copied correctly\"\"\"\n",
    "\n",
    "dataset_link = 'http://mattmahoney.net/dc/'\n",
    "zip_file = 'text8.zip'\n",
    "\n",
    "def data_download(zip_file):\n",
    "    \"\"\"Downloading the required file\"\"\"\n",
    "    if not os.path.exists(zip_file):\n",
    "        zip_file, _ = urlretrieve(dataset_link + zip_file, zip_file)\n",
    "        print('File downloaded successfully!')\n",
    "    return None\n",
    "\n",
    "data_download(zip_file)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "\"\"\"Extracting the dataset in separate folder\"\"\"\n",
    "extracted_folder = 'dataset'\n",
    "\n",
    "if not os.path.isdir(extracted_folder):\n",
    "    with zipfile.ZipFile(zip_file) as zf:\n",
    "        zf.extractall(extracted_folder)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "with open('dataset/text8') as ft_ :\n",
    "    full_text = ft_.read()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "def text_processing(ft8_text):\n",
    "    \"\"\"Replacing punctuation marks with tokens\"\"\"\n",
    "    ft8_text = ft8_text.lower()\n",
    "    ft8_text = ft8_text.replace('.', ' <period> ')\n",
    "    ft8_text = ft8_text.replace(',', ' <comma> ')\n",
    "    ft8_text = ft8_text.replace('\"', ' <quotation> ')\n",
    "    ft8_text = ft8_text.replace(';', ' <semicolon> ')\n",
    "    ft8_text = ft8_text.replace('!', ' <exclamation> ')\n",
    "    ft8_text = ft8_text.replace('?', ' <question> ')\n",
    "    ft8_text = ft8_text.replace('(', ' <paren_l> ')\n",
    "    ft8_text = ft8_text.replace(')', ' <paren_r> ')\n",
    "    ft8_text = ft8_text.replace('--', ' <hyphen> ')\n",
    "    ft8_text = ft8_text.replace(':', ' <colon> ')\n",
    "    ft8_text_tokens = ft8_text.split()\n",
    "    \n",
    "    return ft8_text_tokens"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "ft_tokens = text_processing(full_text)\n",
    "\"\"\"Shortlisting words with frequency more than 7\"\"\"\n",
    "word_cnt = collections.Counter(ft_tokens)\n",
    "shortlisted_words = [w for w in ft_tokens if word_cnt[w] > 7 ]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "['anarchism', 'originated', 'as', 'a', 'term', 'of', 'abuse', 'first', 'used', 'against', 'early', 'working', 'class', 'radicals', 'including']\n"
     ]
    }
   ],
   "source": [
    "print(shortlisted_words[:15])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Total number of shortlisted words :  16616688\n",
      "Unique number of shortlisted words :  53721\n"
     ]
    }
   ],
   "source": [
    "print(\"Total number of shortlisted words : \",len(shortlisted_words))\n",
    "print(\"Unique number of shortlisted words : \",len(set(shortlisted_words)))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "def dict_creation(shortlisted_words):\n",
    "    \"\"\"The function creates a dictionary of the words present in dataset along with their frequency order\"\"\"\n",
    "    counts = collections.Counter(shortlisted_words)\n",
    "    vocabulary = sorted(counts, key=counts.get, reverse=True)\n",
    "    rev_dictionary_ = {ii: word for ii, word in enumerate(vocabulary)}\n",
    "    dictionary_ = {word: ii for ii, word in rev_dictionary_.items()}\n",
    "    return dictionary_, rev_dictionary_"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "dictionary_, rev_dictionary_ = dict_creation(shortlisted_words)\n",
    "words_cnt = [dictionary_[word] for word in shortlisted_words]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### SkipGram"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "\"\"\"Creating the threshold and performing the subsampling\"\"\"\n",
    "thresh = 0.00005\n",
    "word_counts = collections.Counter(words_cnt)\n",
    "total_count = len(words_cnt)\n",
    "freqs = {word: count / total_count for word, count in word_counts.items()}\n",
    "p_drop = {word: 1 - np.sqrt(thresh/freqs[word]) for word in word_counts}\n",
    "train_words = [word for word in words_cnt if p_drop[word] < random.random()]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "def skipG_target_set_generation(batch_, batch_index, word_window): \n",
    "    \"\"\"The function combines the words of given word_window size next to the index, for the SkipGram model\"\"\"\n",
    "    random_num = np.random.randint(1, word_window+1)\n",
    "    words_start = batch_index - random_num if (batch_index - random_num) > 0 else 0\n",
    "    words_stop = batch_index + random_num\n",
    "    window_target = set(batch_[words_start:batch_index] + batch_[batch_index+1:words_stop+1])\n",
    "    return list(window_target)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "def skipG_batch_creation(short_words, batch_length, word_window):\n",
    "    \"\"\"The function internally makes use of the skipG_target_set_generation() function and combines each of the label \n",
    "    words in the shortlisted_words with the words of word_window size around\"\"\"\n",
    "    batch_cnt = len(short_words)//batch_length\n",
    "    short_words = short_words[:batch_cnt*batch_length]  \n",
    "    \n",
    "    for word_index in range(0, len(short_words), batch_length):\n",
    "        input_words, label_words = [], []\n",
    "        word_batch = short_words[word_index:word_index+batch_length]\n",
    "        for index_ in range(len(word_batch)):\n",
    "            batch_input = word_batch[index_]\n",
    "            batch_label = skipG_target_set_generation(word_batch, index_, word_window)\n",
    "            # Appending the label and inputs to the initial list. Replicating input to the size of labels in the window \n",
    "            label_words.extend(batch_label)\n",
    "            input_words.extend([batch_input]*len(batch_label))\n",
    "        yield input_words, label_words"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "tf_graph = tf.Graph()\n",
    "with tf_graph.as_default():\n",
    "    input_ = tf.placeholder(tf.int32, [None], name='input_')\n",
    "    label_ = tf.placeholder(tf.int32, [None, None], name='label_')\n",
    "\n",
    "with tf_graph.as_default():\n",
    "    word_embed = tf.Variable(tf.random_uniform((len(rev_dictionary_), 300), -1, 1))\n",
    "    embedding = tf.nn.embedding_lookup(word_embed, input_)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The tf.train.AdamOptimizer uses Kingma and Ba's Adam algorithm (http://arxiv.org/pdf/1412.6980v8.pdf) to control the\n",
    "learning rate.\n",
    "For further reference, one can refer to the following paper as well by Bengio, http://arxiv.org/pdf/1206.5533.pdf"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "\"\"\"The code includes the following  :\n",
    " # Initializing weights and bias to be used in the softmax layer\n",
    " # Loss function calculation using the Negative Sampling\n",
    " # Usage of Adam Optimizer\n",
    " # Negative sampling on 100 words, to be included in the loss function\n",
    " # 300 is the word embedding vector size\n",
    "\"\"\"\n",
    "vocabulary_size = len(rev_dictionary_)\n",
    "\n",
    "with tf_graph.as_default():\n",
    "    sf_weights = tf.Variable(tf.truncated_normal((vocabulary_size, 300), stddev=0.1) )\n",
    "    sf_bias = tf.Variable(tf.zeros(vocabulary_size) )\n",
    "\n",
    "    loss_fn = tf.nn.sampled_softmax_loss(weights=sf_weights, biases=sf_bias, \n",
    "                                         labels=label_, inputs=embedding, \n",
    "                                         num_sampled=100, num_classes=vocabulary_size)\n",
    "    cost_fn = tf.reduce_mean(loss_fn)\n",
    "    optim = tf.train.AdamOptimizer().minimize(cost_fn)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "\"\"\"The below code performs the following operations :\n",
    " # Performing validation here by making use of a random selection of 16 words from the dictionary of desired size\n",
    " # Selecting 8 words randomly from range of 1000    \n",
    " # Using the cosine distance to calculate the similarity between the words \n",
    "\"\"\"\n",
    "with tf_graph.as_default():\n",
    "    validation_cnt = 16\n",
    "    validation_dict = 100\n",
    "    \n",
    "    validation_words = np.array(random.sample(range(validation_dict), validation_cnt//2))\n",
    "    validation_words = np.append(validation_words, random.sample(range(1000,1000+validation_dict), validation_cnt//2))\n",
    "    validation_data = tf.constant(validation_words, dtype=tf.int32)\n",
    "\n",
    "    normalization_embed = word_embed / (tf.sqrt(tf.reduce_sum(tf.square(word_embed), 1, keep_dims=True)))\n",
    "    validation_embed = tf.nn.embedding_lookup(normalization_embed, validation_data)\n",
    "    word_similarity = tf.matmul(validation_embed, tf.transpose(normalization_embed))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "mkdir: cannot create directory `model_checkpoint': File exists\r\n"
     ]
    }
   ],
   "source": [
    "\"\"\"Creating the model checkpoint directory\"\"\"\n",
    "!mkdir model_checkpoint"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 38,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch 1/2 , Iteration: 100 , Avg. Training loss: 6.1494 , Processing : 0.3485 sec/batch\n",
      "Epoch 1/2 , Iteration: 200 , Avg. Training loss: 6.1851 , Processing : 0.3507 sec/batch\n",
      "Epoch 1/2 , Iteration: 300 , Avg. Training loss: 6.0753 , Processing : 0.3502 sec/batch\n",
      "Epoch 1/2 , Iteration: 400 , Avg. Training loss: 6.0025 , Processing : 0.3535 sec/batch\n",
      "Epoch 1/2 , Iteration: 500 , Avg. Training loss: 5.9307 , Processing : 0.3547 sec/batch\n",
      "Epoch 1/2 , Iteration: 600 , Avg. Training loss: 5.9997 , Processing : 0.3509 sec/batch\n",
      "Epoch 1/2 , Iteration: 700 , Avg. Training loss: 5.8420 , Processing : 0.3537 sec/batch\n",
      "Epoch 1/2 , Iteration: 800 , Avg. Training loss: 5.7162 , Processing : 0.3542 sec/batch\n",
      "Epoch 1/2 , Iteration: 900 , Avg. Training loss: 5.6495 , Processing : 0.3511 sec/batch\n",
      "Epoch 1/2 , Iteration: 1000 , Avg. Training loss: 5.5558 , Processing : 0.3560 sec/batch\n",
      "Epoch 1/2 , Iteration: 1100 , Avg. Training loss: 5.4336 , Processing : 0.3547 sec/batch\n",
      "Epoch 1/2 , Iteration: 1200 , Avg. Training loss: 5.3797 , Processing : 0.3543 sec/batch\n",
      "Epoch 1/2 , Iteration: 1300 , Avg. Training loss: 5.2479 , Processing : 0.3566 sec/batch\n",
      "Epoch 1/2 , Iteration: 1400 , Avg. Training loss: 5.1508 , Processing : 0.3626 sec/batch\n",
      "Epoch 1/2 , Iteration: 1500 , Avg. Training loss: 5.1390 , Processing : 0.3541 sec/batch\n",
      "Epoch 1/2 , Iteration: 1600 , Avg. Training loss: 5.0821 , Processing : 0.3530 sec/batch\n",
      "Epoch 1/2 , Iteration: 1700 , Avg. Training loss: 5.0303 , Processing : 0.3541 sec/batch\n",
      "Epoch 1/2 , Iteration: 1800 , Avg. Training loss: 4.9576 , Processing : 0.3545 sec/batch\n",
      "Epoch 1/2 , Iteration: 1900 , Avg. Training loss: 4.9801 , Processing : 0.3527 sec/batch\n",
      "Epoch 1/2 , Iteration: 2000 , Avg. Training loss: 4.9449 , Processing : 0.3553 sec/batch\n",
      "Nearest to during: stress, shipping, bishoprics, accept, produce, color, buckley, victor,\n",
      "Nearest to six: article, incorporated, raced, interval, layouts, confused, spitz, masculinity,\n",
      "Nearest to all: cm, unprotected, fit, tom, opold, render, perth, temptation,\n",
      "Nearest to th: ponder, orchids, shor, polluted, firefighting, hammering, bonn, suited,\n",
      "Nearest to many: trenches, parentheses, essential, error, chalmers, philo, win, mba,\n",
      "Nearest to into: defunct, uniquely, unsatisfied, aggregate, arabica, fiercely, produced, integrator,\n",
      "Nearest to some: vicinity, collaborators, score, originate, came, fix, samoa, abject,\n",
      "Nearest to while: deprogramming, stood, browsers, yahya, oppose, misleading, handkerchief, standards,\n",
      "Nearest to police: contextual, jurassic, redistribution, theron, argentina, transplantation, kimberley, crypt,\n",
      "Nearest to hit: pio, ducts, wynette, revived, plan, vic, kahan, oscar,\n",
      "Nearest to know: obex, emboldened, grunge, writings, revelation, following, outlined, championships,\n",
      "Nearest to san: sexual, andy, air, demo, manifest, pause, dragonball, garnish,\n",
      "Nearest to versions: materials, translates, knives, metaphor, bacardi, anywhere, yards, revolutionized,\n",
      "Nearest to award: meritorious, eliminating, relocating, stjepan, exploded, district, blitzkrieg, slab,\n",
      "Nearest to centre: proposing, minds, decrees, libertarians, fourths, manuscript, tokyo, ux,\n",
      "Nearest to joseph: his, uniform, growth, wards, nearer, editable, incidentally, computational,\n",
      "Epoch 1/2 , Iteration: 2100 , Avg. Training loss: 4.9462 , Processing : 0.3621 sec/batch\n",
      "Epoch 1/2 , Iteration: 2200 , Avg. Training loss: 4.8930 , Processing : 0.3528 sec/batch\n",
      "Epoch 1/2 , Iteration: 2300 , Avg. Training loss: 4.9109 , Processing : 0.3535 sec/batch\n",
      "Epoch 1/2 , Iteration: 2400 , Avg. Training loss: 4.8750 , Processing : 0.3559 sec/batch\n",
      "Epoch 1/2 , Iteration: 2500 , Avg. Training loss: 4.7950 , Processing : 0.3568 sec/batch\n",
      "Epoch 1/2 , Iteration: 2600 , Avg. Training loss: 4.8529 , Processing : 0.3557 sec/batch\n",
      "Epoch 1/2 , Iteration: 2700 , Avg. Training loss: 4.8271 , Processing : 0.3585 sec/batch\n",
      "Epoch 1/2 , Iteration: 2800 , Avg. Training loss: 4.8079 , Processing : 0.3551 sec/batch\n",
      "Epoch 1/2 , Iteration: 2900 , Avg. Training loss: 4.8142 , Processing : 0.3555 sec/batch\n",
      "Epoch 1/2 , Iteration: 3000 , Avg. Training loss: 4.7943 , Processing : 0.3581 sec/batch\n",
      "Epoch 1/2 , Iteration: 3100 , Avg. Training loss: 4.7571 , Processing : 0.3570 sec/batch\n",
      "Epoch 1/2 , Iteration: 3200 , Avg. Training loss: 4.7595 , Processing : 0.3570 sec/batch\n",
      "Epoch 1/2 , Iteration: 3300 , Avg. Training loss: 4.7382 , Processing : 0.3539 sec/batch\n",
      "Epoch 1/2 , Iteration: 3400 , Avg. Training loss: 4.7413 , Processing : 0.3577 sec/batch\n",
      "Epoch 1/2 , Iteration: 3500 , Avg. Training loss: 4.7340 , Processing : 0.3562 sec/batch\n",
      "Epoch 1/2 , Iteration: 3600 , Avg. Training loss: 4.6823 , Processing : 0.3549 sec/batch\n",
      "Epoch 1/2 , Iteration: 3700 , Avg. Training loss: 4.7054 , Processing : 0.3578 sec/batch\n",
      "Epoch 1/2 , Iteration: 3800 , Avg. Training loss: 4.6938 , Processing : 0.3522 sec/batch\n",
      "Epoch 1/2 , Iteration: 3900 , Avg. Training loss: 4.6320 , Processing : 0.3518 sec/batch\n",
      "Epoch 1/2 , Iteration: 4000 , Avg. Training loss: 4.6492 , Processing : 0.3562 sec/batch\n",
      "Nearest to during: clc, shipping, bishoprics, stress, accept, queensland, buckley, galley,\n",
      "Nearest to six: four, mayer, apotheosis, three, raced, noon, noor, emilio,\n",
      "Nearest to all: cm, unprotected, fit, render, temptation, opold, pong, superhuman,\n",
      "Nearest to th: orchids, shor, ponder, bonn, symbolised, hammering, romanic, polluted,\n",
      "Nearest to many: trenches, parentheses, mba, essential, highly, ngel, pentagons, enjoy,\n",
      "Nearest to into: defunct, uniquely, unsatisfied, aggregate, arabica, fiercely, integrator, gwynne,\n",
      "Nearest to some: koran, collaborators, originate, angled, vicinity, samoa, licenced, fix,\n",
      "Nearest to while: deprogramming, browsers, memetics, sharif, stood, neuralgia, microorganism, afp,\n",
      "Nearest to police: contextual, jurassic, transplantation, kimberley, theron, argentina, athleticism, syntactical,\n",
      "Nearest to hit: hardened, pio, wynette, cynthia, vic, kahan, ducts, revived,\n",
      "Nearest to know: obex, emboldened, grunge, remix, revelation, viaduct, oriente, ceiba,\n",
      "Nearest to san: andy, dragonball, air, singin, dickson, oliphant, demo, snowstorm,\n",
      "Nearest to versions: materials, revolutionized, metaphor, knives, translates, despotic, middlesex, heckman,\n",
      "Nearest to award: meritorious, eliminating, relocating, alchemist, stjepan, tenor, lepers, district,\n",
      "Nearest to centre: proposing, fourths, tokyo, libertarians, decrees, ux, minds, styx,\n",
      "Nearest to joseph: his, musician, miss, nearer, slapped, berzelius, laud, aldrin,\n",
      "Epoch 1/2 , Iteration: 4100 , Avg. Training loss: 4.6177 , Processing : 0.3622 sec/batch\n",
      "Epoch 1/2 , Iteration: 4200 , Avg. Training loss: 4.6661 , Processing : 0.3561 sec/batch\n",
      "Epoch 1/2 , Iteration: 4300 , Avg. Training loss: 4.6397 , Processing : 0.3570 sec/batch\n",
      "Epoch 1/2 , Iteration: 4400 , Avg. Training loss: 4.6711 , Processing : 0.3568 sec/batch\n",
      "Epoch 1/2 , Iteration: 4500 , Avg. Training loss: 4.6006 , Processing : 0.3587 sec/batch\n",
      "Epoch 1/2 , Iteration: 4600 , Avg. Training loss: 4.6477 , Processing : 0.3570 sec/batch\n",
      "Epoch 1/2 , Iteration: 4700 , Avg. Training loss: 4.6235 , Processing : 0.3564 sec/batch\n",
      "Epoch 1/2 , Iteration: 4800 , Avg. Training loss: 4.6247 , Processing : 0.3565 sec/batch\n",
      "Epoch 1/2 , Iteration: 4900 , Avg. Training loss: 4.6251 , Processing : 0.3576 sec/batch\n",
      "Epoch 1/2 , Iteration: 5000 , Avg. Training loss: 4.5484 , Processing : 0.3579 sec/batch\n",
      "Epoch 1/2 , Iteration: 5100 , Avg. Training loss: 4.5115 , Processing : 0.3550 sec/batch\n",
      "Epoch 1/2 , Iteration: 5200 , Avg. Training loss: 4.5600 , Processing : 0.3538 sec/batch\n",
      "Epoch 1/2 , Iteration: 5300 , Avg. Training loss: 4.4963 , Processing : 0.3537 sec/batch\n",
      "Epoch 1/2 , Iteration: 5400 , Avg. Training loss: 4.5494 , Processing : 0.3579 sec/batch\n",
      "Epoch 1/2 , Iteration: 5500 , Avg. Training loss: 4.5034 , Processing : 0.3563 sec/batch\n",
      "Epoch 1/2 , Iteration: 5600 , Avg. Training loss: 4.5290 , Processing : 0.3588 sec/batch\n",
      "Epoch 1/2 , Iteration: 5700 , Avg. Training loss: 4.5858 , Processing : 0.3578 sec/batch\n",
      "Epoch 1/2 , Iteration: 5800 , Avg. Training loss: 4.5694 , Processing : 0.3572 sec/batch\n",
      "Epoch 1/2 , Iteration: 5900 , Avg. Training loss: 4.6227 , Processing : 0.3550 sec/batch\n",
      "Epoch 1/2 , Iteration: 6000 , Avg. Training loss: 4.5502 , Processing : 0.3570 sec/batch\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Nearest to during: shipping, clc, bishoprics, fandoms, galley, broke, noddy, queensland,\n",
      "Nearest to six: four, mayer, auguste, apotheosis, ellery, noor, mighty, forehead,\n",
      "Nearest to all: unprotected, fit, render, cm, temptation, pong, opold, memos,\n",
      "Nearest to th: symbolised, conquest, orchids, shor, romanic, bonn, hammering, caithness,\n",
      "Nearest to many: parentheses, trenches, highly, vanities, mba, pentagons, perpetrator, ngel,\n",
      "Nearest to into: defunct, uniquely, aggregate, arabica, unsatisfied, intervened, integrator, gulf,\n",
      "Nearest to some: collaborators, koran, originate, really, abject, angled, syriac, proportion,\n",
      "Nearest to while: memetics, microorganism, deprogramming, stood, sharif, browsers, jabbar, afp,\n",
      "Nearest to police: jurassic, contextual, transplantation, kimberley, justice, theron, inoue, hardliners,\n",
      "Nearest to hit: cynthia, vic, pio, wynette, hardened, solicitation, editable, ducts,\n",
      "Nearest to know: obex, emboldened, grunge, remix, ceiba, revelation, stirner, sylvester,\n",
      "Nearest to san: andy, singin, dragonball, air, garnish, portland, traveled, oliphant,\n",
      "Nearest to versions: materials, revolutionized, metaphor, despotic, translates, knives, heckman, bacardi,\n",
      "Nearest to award: meritorious, relocating, alchemist, tenor, prize, stjepan, s, wildcats,\n",
      "Nearest to centre: ux, fourths, tokyo, decrees, libertarians, proposing, enraged, styx,\n",
      "Nearest to joseph: his, miss, slapped, laud, nearer, aldrin, musician, vera,\n",
      "Epoch 1/2 , Iteration: 6100 , Avg. Training loss: 4.4495 , Processing : 0.3658 sec/batch\n",
      "Epoch 1/2 , Iteration: 6200 , Avg. Training loss: 4.5045 , Processing : 0.3570 sec/batch\n",
      "Epoch 1/2 , Iteration: 6300 , Avg. Training loss: 4.5111 , Processing : 0.3538 sec/batch\n",
      "Epoch 1/2 , Iteration: 6400 , Avg. Training loss: 4.5392 , Processing : 0.3583 sec/batch\n",
      "Epoch 1/2 , Iteration: 6500 , Avg. Training loss: 4.4823 , Processing : 0.3545 sec/batch\n",
      "Epoch 1/2 , Iteration: 6600 , Avg. Training loss: 4.3216 , Processing : 0.3575 sec/batch\n",
      "Epoch 1/2 , Iteration: 6700 , Avg. Training loss: 4.4893 , Processing : 0.3564 sec/batch\n",
      "Epoch 1/2 , Iteration: 6800 , Avg. Training loss: 4.4710 , Processing : 0.3571 sec/batch\n",
      "Epoch 1/2 , Iteration: 6900 , Avg. Training loss: 4.4826 , Processing : 0.3584 sec/batch\n",
      "Epoch 1/2 , Iteration: 7000 , Avg. Training loss: 4.4353 , Processing : 0.3568 sec/batch\n",
      "Epoch 1/2 , Iteration: 7100 , Avg. Training loss: 4.5042 , Processing : 0.3576 sec/batch\n",
      "Epoch 2/2 , Iteration: 7200 , Avg. Training loss: 4.4990 , Processing : 0.1222 sec/batch\n",
      "Epoch 2/2 , Iteration: 7300 , Avg. Training loss: 4.4080 , Processing : 0.3554 sec/batch\n",
      "Epoch 2/2 , Iteration: 7400 , Avg. Training loss: 4.3787 , Processing : 0.3559 sec/batch\n",
      "Epoch 2/2 , Iteration: 7500 , Avg. Training loss: 4.3891 , Processing : 0.3554 sec/batch\n",
      "Epoch 2/2 , Iteration: 7600 , Avg. Training loss: 4.3640 , Processing : 0.3565 sec/batch\n",
      "Epoch 2/2 , Iteration: 7700 , Avg. Training loss: 4.3903 , Processing : 0.3601 sec/batch\n",
      "Epoch 2/2 , Iteration: 7800 , Avg. Training loss: 4.3541 , Processing : 0.3560 sec/batch\n",
      "Epoch 2/2 , Iteration: 7900 , Avg. Training loss: 4.3315 , Processing : 0.3548 sec/batch\n",
      "Epoch 2/2 , Iteration: 8000 , Avg. Training loss: 4.3738 , Processing : 0.3571 sec/batch\n",
      "Nearest to during: shipping, clc, bishoprics, noddy, tishri, polis, crystallizes, fandoms,\n",
      "Nearest to six: four, three, mayer, hydro, auguste, noor, louisbourg, apotheosis,\n",
      "Nearest to all: cm, fit, render, unprotected, pong, this, temptation, each,\n",
      "Nearest to th: symbolised, bonn, orchids, conquest, assimilation, romanic, last, century,\n",
      "Nearest to many: parentheses, highly, trenches, decades, philo, pentagons, turbojet, mba,\n",
      "Nearest to into: defunct, uniquely, arabica, aggregate, intervened, unsatisfied, produced, integrator,\n",
      "Nearest to some: angled, collaborators, came, originate, koran, visitor, jh, illogical,\n",
      "Nearest to while: memetics, deprogramming, neuralgia, microorganism, stood, them, afp, irv,\n",
      "Nearest to police: contextual, jurassic, transplantation, kimberley, justice, hardliners, inoue, athleticism,\n",
      "Nearest to hit: wynette, hardened, vic, solicitation, pio, sanfl, puppets, cynthia,\n",
      "Nearest to know: obex, we, emboldened, grunge, remix, ve, ceiba, your,\n",
      "Nearest to san: singin, air, portland, andy, dragonball, bertram, garnish, maggiore,\n",
      "Nearest to versions: materials, metaphor, despotic, revolutionized, heckman, mvs, cessna, knives,\n",
      "Nearest to award: meritorious, alchemist, academy, relocating, tenor, wildcats, stjepan, resolving,\n",
      "Nearest to centre: tokyo, nesting, ux, fourths, areas, memorabilia, proposing, decrees,\n",
      "Nearest to joseph: his, laud, miss, slapped, vera, aldrin, nearer, musician,\n",
      "Epoch 2/2 , Iteration: 8100 , Avg. Training loss: 4.3503 , Processing : 0.3635 sec/batch\n",
      "Epoch 2/2 , Iteration: 8200 , Avg. Training loss: 4.2501 , Processing : 0.3556 sec/batch\n",
      "Epoch 2/2 , Iteration: 8300 , Avg. Training loss: 4.3966 , Processing : 0.3553 sec/batch\n",
      "Epoch 2/2 , Iteration: 8400 , Avg. Training loss: 4.3942 , Processing : 0.3568 sec/batch\n",
      "Epoch 2/2 , Iteration: 8500 , Avg. Training loss: 4.3692 , Processing : 0.3536 sec/batch\n",
      "Epoch 2/2 , Iteration: 8600 , Avg. Training loss: 4.3682 , Processing : 0.3549 sec/batch\n",
      "Epoch 2/2 , Iteration: 8700 , Avg. Training loss: 4.3614 , Processing : 0.3575 sec/batch\n",
      "Epoch 2/2 , Iteration: 8800 , Avg. Training loss: 4.3529 , Processing : 0.3587 sec/batch\n",
      "Epoch 2/2 , Iteration: 8900 , Avg. Training loss: 4.2688 , Processing : 0.3577 sec/batch\n",
      "Epoch 2/2 , Iteration: 9000 , Avg. Training loss: 4.2699 , Processing : 0.3565 sec/batch\n",
      "Epoch 2/2 , Iteration: 9100 , Avg. Training loss: 4.3176 , Processing : 0.3574 sec/batch\n",
      "Epoch 2/2 , Iteration: 9200 , Avg. Training loss: 4.3210 , Processing : 0.3542 sec/batch\n",
      "Epoch 2/2 , Iteration: 9300 , Avg. Training loss: 4.2994 , Processing : 0.3540 sec/batch\n",
      "Epoch 2/2 , Iteration: 9400 , Avg. Training loss: 4.3305 , Processing : 0.3564 sec/batch\n",
      "Epoch 2/2 , Iteration: 9500 , Avg. Training loss: 4.3407 , Processing : 0.3581 sec/batch\n",
      "Epoch 2/2 , Iteration: 9600 , Avg. Training loss: 4.3181 , Processing : 0.3558 sec/batch\n",
      "Epoch 2/2 , Iteration: 9700 , Avg. Training loss: 4.3113 , Processing : 0.3589 sec/batch\n",
      "Epoch 2/2 , Iteration: 9800 , Avg. Training loss: 4.3138 , Processing : 0.3573 sec/batch\n",
      "Epoch 2/2 , Iteration: 9900 , Avg. Training loss: 4.3067 , Processing : 0.3565 sec/batch\n",
      "Epoch 2/2 , Iteration: 10000 , Avg. Training loss: 4.3162 , Processing : 0.3587 sec/batch\n",
      "Nearest to during: shipping, noddy, bishoprics, stress, clc, fandoms, tishri, crystallizes,\n",
      "Nearest to six: four, three, eight, two, seven, ellery, mayer, hydro,\n",
      "Nearest to all: fit, render, cm, each, unprotected, this, asatru, readings,\n",
      "Nearest to th: bonn, assimilation, symbolised, last, orchids, century, romanic, nineteenth,\n",
      "Nearest to many: parentheses, highly, philo, trenches, enjoy, synth, share, turbojet,\n",
      "Nearest to into: defunct, uniquely, unsatisfied, arabica, integrator, aggregate, each, system,\n",
      "Nearest to some: collaborators, really, fishes, angled, originate, visitor, came, yog,\n",
      "Nearest to while: memetics, stood, deprogramming, microorganism, neuralgia, irv, afp, them,\n",
      "Nearest to police: contextual, jurassic, transplantation, kimberley, justice, inoue, authentication, hardliners,\n",
      "Nearest to hit: wynette, hardened, solicitation, cynthia, airstrip, sanfl, pio, bottoms,\n",
      "Nearest to know: we, obex, emboldened, grunge, your, ve, sylvester, ceiba,\n",
      "Nearest to san: singin, air, portland, dragonball, maggiore, snowstorm, garnish, turnpike,\n",
      "Nearest to versions: materials, metaphor, despotic, heckman, revolutionized, cessna, mvs, knives,\n",
      "Nearest to award: meritorious, alchemist, academy, awards, relocating, organizes, prize, s,\n",
      "Nearest to centre: nesting, ux, tokyo, proposing, areas, fourths, memorabilia, formerly,\n",
      "Nearest to joseph: his, laud, slapped, aldrin, miss, berzelius, inspiration, lithograph,\n",
      "Epoch 2/2 , Iteration: 10100 , Avg. Training loss: 4.3384 , Processing : 0.3636 sec/batch\n",
      "Epoch 2/2 , Iteration: 10200 , Avg. Training loss: 4.3730 , Processing : 0.3548 sec/batch\n",
      "Epoch 2/2 , Iteration: 10300 , Avg. Training loss: 4.2221 , Processing : 0.3561 sec/batch\n",
      "Epoch 2/2 , Iteration: 10400 , Avg. Training loss: 4.2691 , Processing : 0.3573 sec/batch\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch 2/2 , Iteration: 10500 , Avg. Training loss: 4.3164 , Processing : 0.3588 sec/batch\n",
      "Epoch 2/2 , Iteration: 10600 , Avg. Training loss: 4.3178 , Processing : 0.3582 sec/batch\n",
      "Epoch 2/2 , Iteration: 10700 , Avg. Training loss: 4.3456 , Processing : 0.3600 sec/batch\n",
      "Epoch 2/2 , Iteration: 10800 , Avg. Training loss: 4.2900 , Processing : 0.3591 sec/batch\n",
      "Epoch 2/2 , Iteration: 10900 , Avg. Training loss: 4.2685 , Processing : 0.3576 sec/batch\n",
      "Epoch 2/2 , Iteration: 11000 , Avg. Training loss: 4.2607 , Processing : 0.3529 sec/batch\n",
      "Epoch 2/2 , Iteration: 11100 , Avg. Training loss: 4.3599 , Processing : 0.3604 sec/batch\n",
      "Epoch 2/2 , Iteration: 11200 , Avg. Training loss: 4.3196 , Processing : 0.3554 sec/batch\n",
      "Epoch 2/2 , Iteration: 11300 , Avg. Training loss: 4.2417 , Processing : 0.3563 sec/batch\n",
      "Epoch 2/2 , Iteration: 11400 , Avg. Training loss: 4.3110 , Processing : 0.3582 sec/batch\n",
      "Epoch 2/2 , Iteration: 11500 , Avg. Training loss: 4.2762 , Processing : 0.3647 sec/batch\n",
      "Epoch 2/2 , Iteration: 11600 , Avg. Training loss: 4.3268 , Processing : 0.3567 sec/batch\n",
      "Epoch 2/2 , Iteration: 11700 , Avg. Training loss: 4.2742 , Processing : 0.3598 sec/batch\n",
      "Epoch 2/2 , Iteration: 11800 , Avg. Training loss: 4.3071 , Processing : 0.3582 sec/batch\n",
      "Epoch 2/2 , Iteration: 11900 , Avg. Training loss: 4.2859 , Processing : 0.3559 sec/batch\n",
      "Epoch 2/2 , Iteration: 12000 , Avg. Training loss: 4.3219 , Processing : 0.3589 sec/batch\n",
      "Nearest to during: noddy, shipping, fandoms, outbreak, bishoprics, clc, balochi, stress,\n",
      "Nearest to six: four, three, two, eight, seven, one, ellery, five,\n",
      "Nearest to all: fit, each, render, cm, asatru, unprotected, readings, this,\n",
      "Nearest to th: century, last, assimilation, bonn, symbolised, nineteenth, conquest, orchids,\n",
      "Nearest to many: highly, parentheses, roman, ngel, philo, synth, decades, turbojet,\n",
      "Nearest to into: defunct, unsatisfied, uniquely, intervened, meltwater, system, aggregate, arabica,\n",
      "Nearest to some: collaborators, came, yog, fishes, visitor, koran, proportion, originate,\n",
      "Nearest to while: memetics, stood, microorganism, demonic, deprogramming, them, irv, fallopian,\n",
      "Nearest to police: contextual, hardliners, jurassic, justice, transplantation, kimberley, narrations, propped,\n",
      "Nearest to hit: wynette, hardened, moorcock, cynthia, billboard, solicitation, airstrip, bottoms,\n",
      "Nearest to know: we, your, emboldened, ve, obex, flutist, sylvester, fuck,\n",
      "Nearest to san: singin, maggiore, air, turnpike, dragonball, garnish, portland, andy,\n",
      "Nearest to versions: materials, metaphor, despotic, mvs, revolutionized, cessna, heckman, translates,\n",
      "Nearest to award: meritorious, academy, awards, alchemist, prize, organizes, relocating, tenor,\n",
      "Nearest to centre: proposing, nesting, areas, tokyo, ux, departures, formerly, fourths,\n",
      "Nearest to joseph: his, laud, slapped, aldrin, miss, berzelius, lithograph, vera,\n",
      "Epoch 2/2 , Iteration: 12100 , Avg. Training loss: 4.3210 , Processing : 0.3647 sec/batch\n",
      "Epoch 2/2 , Iteration: 12200 , Avg. Training loss: 4.2127 , Processing : 0.3586 sec/batch\n",
      "Epoch 2/2 , Iteration: 12300 , Avg. Training loss: 4.2269 , Processing : 0.3584 sec/batch\n",
      "Epoch 2/2 , Iteration: 12400 , Avg. Training loss: 4.2646 , Processing : 0.3559 sec/batch\n",
      "Epoch 2/2 , Iteration: 12500 , Avg. Training loss: 4.2938 , Processing : 0.3563 sec/batch\n",
      "Epoch 2/2 , Iteration: 12600 , Avg. Training loss: 4.1812 , Processing : 0.3613 sec/batch\n",
      "Epoch 2/2 , Iteration: 12700 , Avg. Training loss: 4.2334 , Processing : 0.3599 sec/batch\n",
      "Epoch 2/2 , Iteration: 12800 , Avg. Training loss: 4.2846 , Processing : 0.3621 sec/batch\n",
      "Epoch 2/2 , Iteration: 12900 , Avg. Training loss: 4.3090 , Processing : 0.3611 sec/batch\n",
      "Epoch 2/2 , Iteration: 13000 , Avg. Training loss: 4.3351 , Processing : 0.3611 sec/batch\n",
      "Epoch 2/2 , Iteration: 13100 , Avg. Training loss: 4.3600 , Processing : 0.3618 sec/batch\n",
      "Epoch 2/2 , Iteration: 13200 , Avg. Training loss: 4.2548 , Processing : 0.3602 sec/batch\n",
      "Epoch 2/2 , Iteration: 13300 , Avg. Training loss: 4.1595 , Processing : 0.3593 sec/batch\n",
      "Epoch 2/2 , Iteration: 13400 , Avg. Training loss: 4.2373 , Processing : 0.3569 sec/batch\n",
      "Epoch 2/2 , Iteration: 13500 , Avg. Training loss: 4.2600 , Processing : 0.3582 sec/batch\n",
      "Epoch 2/2 , Iteration: 13600 , Avg. Training loss: 4.2779 , Processing : 0.3583 sec/batch\n",
      "Epoch 2/2 , Iteration: 13700 , Avg. Training loss: 4.1255 , Processing : 0.3597 sec/batch\n",
      "Epoch 2/2 , Iteration: 13800 , Avg. Training loss: 4.2137 , Processing : 0.3605 sec/batch\n",
      "Epoch 2/2 , Iteration: 13900 , Avg. Training loss: 4.2042 , Processing : 0.3583 sec/batch\n",
      "Epoch 2/2 , Iteration: 14000 , Avg. Training loss: 4.2760 , Processing : 0.3599 sec/batch\n",
      "Nearest to during: noddy, shipping, fandoms, outbreak, early, stress, developing, balochi,\n",
      "Nearest to six: four, three, eight, two, one, seven, five, ellery,\n",
      "Nearest to all: each, fit, render, cm, asatru, unprotected, day, this,\n",
      "Nearest to th: last, assimilation, century, symbolised, bonn, nineteenth, gregorian, elisabetta,\n",
      "Nearest to many: highly, parentheses, locusts, philo, synth, share, combined, homonyms,\n",
      "Nearest to into: defunct, unsatisfied, uniquely, system, each, meltwater, produced, arabica,\n",
      "Nearest to some: came, collaborators, fishes, really, unreasonable, modifications, koran, yog,\n",
      "Nearest to while: memetics, microorganism, deprogramming, sharif, stood, irv, them, currie,\n",
      "Nearest to police: contextual, hardliners, fatalities, justice, assassination, jurassic, transplantation, arrested,\n",
      "Nearest to hit: wynette, hardened, billboard, revived, moorcock, puppets, airstrip, bottoms,\n",
      "Nearest to know: we, your, emboldened, ve, fuck, obex, why, flutist,\n",
      "Nearest to san: singin, maggiore, turnpike, garnish, dragonball, andy, air, portland,\n",
      "Nearest to versions: materials, mvs, metaphor, despotic, revolutionized, translates, heckman, demo,\n",
      "Nearest to award: meritorious, academy, awards, alchemist, organizes, prize, neutron, lepers,\n",
      "Nearest to centre: proposing, departures, formerly, nesting, ux, decrees, tokyo, limestones,\n",
      "Nearest to joseph: laud, his, slapped, aldrin, vera, berzelius, etched, lithograph,\n",
      "Epoch 2/2 , Iteration: 14100 , Avg. Training loss: 4.2369 , Processing : 0.3656 sec/batch\n",
      "Epoch 2/2 , Iteration: 14200 , Avg. Training loss: 4.2480 , Processing : 0.3605 sec/batch\n",
      "Epoch 2/2 , Iteration: 14300 , Avg. Training loss: 4.2993 , Processing : 0.3607 sec/batch\n"
     ]
    }
   ],
   "source": [
    "epochs = 2            # Increase it as per computation resources. It has been kept low here for users to replicate the process, increase to 100 or more\n",
    "batch_length = 1000\n",
    "word_window = 10\n",
    "\n",
    "with tf_graph.as_default():\n",
    "    saver = tf.train.Saver()\n",
    "\n",
    "with tf.Session(graph=tf_graph) as sess:\n",
    "    iteration = 1\n",
    "    loss = 0\n",
    "    sess.run(tf.global_variables_initializer())\n",
    "\n",
    "    for e in range(1, epochs+1):\n",
    "        batches = skipG_batch_creation(train_words, batch_length, word_window)\n",
    "        start = time.time()\n",
    "        for x, y in batches:\n",
    "            train_loss, _ = sess.run([cost_fn, optim], \n",
    "                                     feed_dict={input_: x, label_: np.array(y)[:, None]})\n",
    "            loss += train_loss\n",
    "            \n",
    "            if iteration % 100 == 0: \n",
    "                end = time.time()\n",
    "                print(\"Epoch {}/{}\".format(e, epochs), \", Iteration: {}\".format(iteration),\n",
    "                      \", Avg. Training loss: {:.4f}\".format(loss/100),\", Processing : {:.4f} sec/batch\".format((end-start)/100))\n",
    "                loss = 0\n",
    "                start = time.time()\n",
    "            \n",
    "            if iteration % 2000 == 0:\n",
    "                similarity_ = word_similarity.eval()\n",
    "                for i in range(validation_cnt):\n",
    "                    validated_words = rev_dictionary_[validation_words[i]]\n",
    "                    top_k = 8 # number of nearest neighbors\n",
    "                    nearest = (-similarity_[i, :]).argsort()[1:top_k+1]\n",
    "                    log = 'Nearest to %s:' % validated_words\n",
    "                    for k in range(top_k):\n",
    "                        close_word = rev_dictionary_[nearest[k]]\n",
    "                        log = '%s %s,' % (log, close_word)\n",
    "                    print(log)\n",
    "            \n",
    "            iteration += 1\n",
    "    save_path = saver.save(sess, \"model_checkpoint/skipGram_text8.ckpt\")\n",
    "    embed_mat = sess.run(normalization_embed)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": 39,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "INFO:tensorflow:Restoring parameters from model_checkpoint/skipGram_text8.ckpt\n"
     ]
    }
   ],
   "source": [
    "\"\"\"The Saver class adds ops to save and restore variables to and from checkpoints.\"\"\"\n",
    "with tf_graph.as_default():\n",
    "    saver = tf.train.Saver()\n",
    "\n",
    "with tf.Session(graph=tf_graph) as sess:\n",
    "    \"\"\"Restoring the trained network\"\"\"\n",
    "    saver.restore(sess, tf.train.latest_checkpoint('model_checkpoint'))\n",
    "    embed_mat = sess.run(word_embed)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Using the vector representation of 250 words to show their distribution across the new vector space"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 50,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "\n",
    "word_graph = 250\n",
    "tsne = TSNE()\n",
    "word_embedding_tsne = tsne.fit_transform(embed_mat[:word_graph, :])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 45,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f9fc0aaa5c0>"
      ]
     },
     "metadata": {
      "image/png": {
       "height": 576,
       "width": 609
      }
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig, ax = plt.subplots(figsize=(10, 10))\n",
    "for idx in range(word_graph):\n",
    "    plt.scatter(*word_embedding_tsne[idx, :], color='steelblue')\n",
    "    plt.annotate(rev_dictionary_[idx], (word_embedding_tsne[idx, 0], word_embedding_tsne[idx, 1]), alpha=0.6)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "(Optional)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "with open(os.path.join('model_checkpoint', \"metainfo.tsv\"), 'w') as f:\n",
    "    for i in range(len(rev_dictionary_)):\n",
    "        f.write(rev_dictionary_[i] + '\\n')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "summary_writer = tf.summary.FileWriter('model_checkpoint', sess.graph)\n",
    "\n",
    "config = projector.ProjectorConfig()\n",
    "embedding_conf = config.embeddings.add()\n",
    "embedding_conf.metadata_path = os.path.join('model_checkpoint', 'metainfo.tsv')\n",
    "projector.visualize_embeddings(summary_writer, config)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.6.3"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 2
}
